**GSE syntax-Couples Survey


**"Future Roles" (McBride and Mills)

**Reverse code items such that higher scores indicate the mother mostly does the task (creates a new set of reverse coded variables:

DATASET ACTIVATE DataSet1.
RECODE fr1 fr2 fr3 fr4 fr5 fr6 fr7 fr8 fr9 fr10 fr11 fr12 fr13 fr14 fr15 fr16 (1=5) (2=4) (3=3) (4=2) 
    (5=1) INTO revfr1 revfr2 revfr3 revfr4 revfr5 revfr6 revfr7 revfr8 revfr9 revfr10 revfr11 revfr12 
    revfr13 revfr14 revfr15 revfr16.
VARIABLE LABELS  revfr1 'reverse scored item 1' /revfr2 'reverse scored item 2' /revfr3 'reverse '+
    'scored item 3' /revfr4 'reverse scored item 4' /revfr5 'reverse scored item 5' /revfr6 
    'reverse scored item 6' /revfr7 'reverse scored item 7' /revfr8 'reverse scored item 8' /revfr9 
    'reverse scored item 9' /revfr10 'reverse scored item 10' /revfr11 'reverse scored item 11' 
    /revfr12 'reverse scored item 12' /revfr13 'reverse scored item 13' /revfr14 'reverse scored '+
    'item 14' /revfr15 'reverse scored item 15' /revfr16 'reverse scored item 16'.
EXECUTE.

**compute scale scores for the total measure, the "mom" scale and the "dad" scale:

Compute Parent_Role_tot=MEAN.12(revfr1, revfr2, revfr3, revfr4, revfr5, revfr6, revfr7, revfr8, revfr9, revfr10, revfr11, revfr12, 
    revfr13, revfr14, revfr15, revfr16).
EXECUTE.

**these are chores that moms do**

Compute Parent_Role_mom=MEAN.9(revfr1, revfr2, revfr3, revfr4, revfr5, revfr6, revfr7, revfr8, revfr9, revfr10, revfr11, revfr12).  
EXECUTE.

**chores that dads do; these are not the reverse scored items**

Compute Parent_Role_dad = Mean.3(fr13, fr14, fr15, fr16).
EXECUTE.

**repeat for the men/partners

RECODE m_fr1 m_fr2 m_fr3 m_fr4 m_fr5 m_fr6 m_fr7 m_fr8 m_fr9 m_fr10 m_fr11 m_fr12 m_fr13 m_fr14 m_fr15 m_fr16 (1=5) (2=4) (3=3) (4=2) 
    (5=1) INTO m_revfr1 m_revfr2 m_revfr3 m_revfr4 m_revfr5 m_revfr6 m_revfr7 m_revfr8 m_revfr9 m_revfr10 m_revfr11 m_revfr12 
    m_revfr13 m_revfr14 m_revfr15 m_revfr16.
VARIABLE LABELS  m_revfr1 'reverse scored item 1' /m_revfr2 'reverse scored item 2' /m_revfr3 'reverse '+
    'scored item 3' /m_revfr4 'reverse scored item 4' /m_revfr5 'reverse scored item 5' /m_revfr6 
    'reverse scored item 6' /m_revfr7 'reverse scored item 7' /m_revfr8 'reverse scored item 8' /m_revfr9 
    'reverse scored item 9' /revfr10 'reverse scored item 10' /revfr11 'reverse scored item 11' 
    /m_revfr12 'reverse scored item 12' /m_revfr13 'reverse scored item 13' /m_revfr14 'reverse scored '+
    'item 14' /m_revfr15 'reverse scored item 15' /m_revfr16 'reverse scored item 16'.
EXECUTE.

**compute scale scores for the total measure, the "mom" scale and the "dad" scale:

Compute m_Parent_Role_tot=MEAN.12(m_revfr1, m_revfr2, m_revfr3, m_revfr4, m_revfr5, m_revfr6, m_revfr7, m_revfr8, m_revfr9, m_revfr10, m_revfr11, m_revfr12, 
    m_revfr13, m_revfr14, m_revfr15, m_revfr16).
EXECUTE.

**these are chores that moms do**

Compute m_Parent_Role_mom=MEAN.9(m_revfr1, m_revfr2, m_revfr3, m_revfr4, m_revfr5, m_revfr6, m_revfr7, m_revfr8, m_revfr9, m_revfr10, m_revfr11, m_revfr12).  
EXECUTE.

**chores that dads do; these are not the reverse scored items**

Compute m_Parent_Role_dad = Mean.3(m_fr13, m_fr14, m_fr15, m_fr16).
EXECUTE.




**"Roles Inventory" (Glick and Fiske sexism scales)

**Reverse score items 3,6,7,13,18,21   

DATASET ACTIVATE DataSet1.
RECODE ri3 ri6 ri7 ri13 ri18 ri21 (1=5) (2=4) (3=3) (4=2) (5=1) INTO revri3 revri6 revri7 revri13 
    revri18 revri21.
VARIABLE LABELS  revri3 'reverse score for ri3' /revri6 'reverse score for 6' /revri7 'reverse '+
    'score for ri7' /revri13 'reverse score for ri13' /revri18 'reverse score for ri18' /revri21 
    'reverse score for ri3'.
EXECUTE.


**compute scale scores for Hostive Sexism, Benevolent Sexism and Total

COMPUTE Sexism_Host=Mean.8(ri2,ri4,ri5,revri7,ri10,ri11,ri14,ri15,ri16,revri18,revri21).
EXECUTE.


COMPUTE Sexism_Ben=Mean.8(ri1,revri3,revri6,ri8,ri9,ri12,revri13,ri17,ri19,ri20).
EXECUTE.


COMPUTE Sexism_Tot=Mean.16(ri2,ri4,ri5,revri7,ri10,ri11,ri14,ri15,ri16,revri18,revri21,ri1,revri3,revri6,ri8,ri9,ri12,revri13,ri17,ri19,ri20).
EXECUTE.

**repeat for the male partners

RECODE m_ri3 m_ri6 m_ri7 m_ri13 m_ri18 m_ri21 (1=5) (2=4) (3=3) (4=2) (5=1) INTO m_revri3 m_revri6 m_revri7 m_revri13 
    m_revri18 m_revri21.
VARIABLE LABELS  m_revri3 'reverse score for ri3' /m_revri6 'reverse score for 6' /m_revri7 'reverse '+
    'score for ri7' /m_revri13 'reverse score for ri13' /m_revri18 'reverse score for ri18' /m_revri21 
    'reverse score for ri3'.
EXECUTE.


**compute scale scores for Hostive Sexism, Benevolent Sexism and Total

COMPUTE m_Sexism_Host=Mean.8(m_ri2, m_ri4, m_ri5, m_revri7,m_ri10,m_ri11,m_ri14,m_ri15,m_ri16,m_revri18,m_revri21).
EXECUTE.


COMPUTE m_Sexism_Ben=Mean.8(m_ri1,m_revri3,m_revri6,m_ri8,m_ri9,m_ri12,m_revri13,m_ri17,m_ri19,m_ri20).
EXECUTE.


COMPUTE m_Sexism_Tot=Mean.16(m_ri2,m_ri4,m_ri5,m_revri7,m_ri10,m_ri11,m_ri14,m_ri15,m_ri16,m_revri18,m_revri21,m_ri1,m_revri3,m_revri6,m_ri8,m_ri9,m_ri12,m_revri13,m_ri17,m_ri19,m_ri20).
EXECUTE.




**Love 'em or Leave 'em


DATASET ACTIVATE DataSet1.
RECODE leave2 to leave6 leave7 leave8 leave13 leave15 to leave17 
     (1=4) (2=3) (3=2) (4=1) (MISSING=SYSMIS) 
    INTO R_leave2 to R_leave6 R_leave7 R_leave8 R_leave13 R_leave15 to R_leave17. 
EXECUTE.

COMPUTE luv_sal_ni=MEAN.2 (leave1, R_leave7).
Compute luv_sal_mo = Mean.2( R_leave4, leave14).
Compute luv_sal_tr = Mean.2( R_leave16, leave10).

Compute luv_pd_ni = Mean.2( R_leave5, leave11).
Compute luv_pd_mo = Mean.2( R_leave8, R_leave17).
Compute luv_pd_tr = Mean.2( R_leave2, R_leave13).

Compute luv_he_ni = Mean.2( R_leave3, leave18).
Compute luv_he_mo = Mean.2( R_leave6, leave12).
Compute luv_he_tr = Mean.2( R_leave15, leave9).
EXECUTE.

COMPUTE Luv_sal=MEAN.3(luv_sal_mo, luv_sal_tr, luv_sal_ni).
COMPUTE Luv_pd=MEAN.3(luv_pd_mo, luv_pd_tr, luv_pd_ni).
COMPUTE Luv_he=MEAN.3(luv_he_mo, luv_he_tr, luv_he_ni).
EXECUTE.


**repeat for the male partners

RECODE m_leave2 to m_leave6 m_leave7 m_leave8 m_leave13 m_leave15 to m_leave17 
     (1=4) (2=3) (3=2) (4=1) (MISSING=SYSMIS) 
    INTO m_R_leave2 to m_R_leave6 m_R_leave7 m_R_leave8 m_R_leave13 m_R_leave15 to m_R_leave17. 
EXECUTE.

COMPUTE m_luv_sal_ni=MEAN.2 (m_leave1, m_R_leave7).
Compute m_luv_sal_mo = Mean.2(m_R_leave4, m_leave14).
Compute m_luv_sal_tr = Mean.2(m_R_leave16, m_leave10).

Compute m_luv_pd_ni = Mean.2(m_R_leave5, m_leave11).
Compute m_luv_pd_mo = Mean.2( m_R_leave8, m_R_leave17).
Compute m_luv_pd_tr = Mean.2( m_R_leave2, m_R_leave13).

Compute m_luv_he_ni = Mean.2( m_R_leave3, m_leave18).
Compute m_luv_he_mo = Mean.2( m_R_leave6, m_leave12).
Compute m_luv_he_tr = Mean.2( m_R_leave15, m_leave9).
EXECUTE.

COMPUTE m_Luv_sal=MEAN.3(m_luv_sal_mo, m_luv_sal_tr, m_luv_sal_ni).
COMPUTE m_Luv_pd=MEAN.3(m_luv_pd_mo, m_luv_pd_tr, m_luv_pd_ni).
COMPUTE m_Luv_he=MEAN.3(m_luv_he_mo, m_luv_he_tr, m_luv_he_ni).
EXECUTE.













